• We are looking for an Analytics Reporting Engineer to join our data team. • Reporting to the Hiring Manager, you will be responsible for applying best practices in data modeling, data transformation, data testing for serving quality data to customer reporting interfaces. • You will be responsible for building and maintaining composable data models, optimizing SQL query performance and maintaining python APIs for serving data to customers. • You will transform raw data into business insights, working closely with stakeholders to serve data to critical customer reporting interfaces. • Build new models and optimize existing ones using SQL and Python. • Apply software engineering principles like version control and continuous integration to the analytics codebase. • Expand our data warehouse with clean data ready for analysis. • Apply advanced data testing strategies to ensure resulting datastores are aligned with expected business logic. • Implement validation checks and automated testing procedures to manage data quality in data transformation and API layers. • Work with stakeholders to define business logic and data expectations. • Help drive a change in the usage of data by actively surfacing insights to stakeholders. • Lead initiatives and problem definition, scoping, design, and planning. • Build tools and automation to run data infrastructure. • Manage large-scale data migrations in relational datastores.

• Design, develop, and maintain scalable backend services using Python and/or Node.js • Build and consume RESTful APIs with a focus on performance, reliability, and security • Develop and integrate microservices-based architectures using Spring Boot where applicable • Containerize applications using Docker and manage deployments using Kubernetes • Design, optimize, and manage data storage solutions using SQL, NoSQL, and Vector Databases • Implement secure coding practices, authentication, authorization, and data protection standards • Collaborate with DevOps teams to implement CI/CD pipelines and cloud deployments on Microsoft Azure • Monitor, troubleshoot, and optimize backend systems for scalability and high availability • Participate in code reviews, architecture discussions, and technical decision-making • Mentor junior developers and contribute to engineering best practices

• Configure, deploy, and maintain enterprise storage hardware and software solutions. • Implement backup and recovery, disaster recovery, data protection, storage consolidation, and performance solutions in accordance with ITSM processes. • Execute storage optimization activities, including upgrades, performance tuning, and system audits. • Serve as a trusted technical advisor to government customers and internal delivery teams. • Advocate customer storage and infrastructure requirements throughout planning and execution. • Partner with Government IT engineering and architecture teams to ensure continuity of storage solutions across customer sites and data centers. • Provide technical consultation on enterprise storage architecture and operational solutions aligned to customer requirements. • Perform requirements analysis and collect technical details to accurately assess customer environments. • Integrate storage platforms into existing IT Service Management (ITSM) data center services and workflows. • Advise on ITSM-aligned best practices to improve storage operations, reliability, and supportability. • Interpret and deliver enterprise storage assessments, including objectives, data collection, analysis, and reporting. • Perform other duties as assigned.

• Design, build, and maintain scalable backend services using C# / .NET Core, along with modern frontend interfaces developed in Angular. • Implement AI-enabled features across multiple products, including document search, MCPs, agents, and chat-based completions. • Leverage tools such as Claude Code and GitHub Copilot on a daily basis to accelerate code generation, refactoring, and technical documentation. • Apply proven architectural patterns such as Domain-Driven Design (DDD) and CQRS to ensure AI-driven features are modular, scalable, and maintainable. • Take full ownership of features from initial design through testing and production deployment, working within a Shift Left development environment.